Course Level 2: Intermediate
Estimated Study Time: 12-15 hours
This course is an introduction to Bayesian statistics. Section 1 discusses several ways of estimating probabilities. Section 2 reviews ideas of conditional probabilities and introduces Bayes’ theorem and its use in updating beliefs about a proposition, when data are observed, or information becomes available. Section 3 introduces the main ideas of the Bayesian inference process. The prior distribution summarizes beliefs about the value of a parameter before data are observed. The likelihood function summarizes information about a parameter contained in observed data and the posterior distribution represents what is known about a parameter after the data have been observed.
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